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This paper describes the new method for measuring the shape of the front surface and the rear surface of a transparent object is difficult because a light does not reflect largely on the surface but mostly penetrate in the object. The proposed use the slightly reflected light on the surface of the transparent object. The experimental results show the usefulness of the proposed method for shape measurement...
We have previously proposed the use of acoustic microbubble delivery in blood vessels to improve the efficacy of acoustic targeted drug therapy. The technical requirement is the detailed visualization of the blood vessel network for navigation around a target such as a tumor. For this purpose, we have used three-dimensional (3D) Doppler-mode volumes to obtain the blood vessel structure. However, since...
This paper presents a nondestructive method of brick wall dampness testing in real building structures. The setup was used to determine the moisture of test brick walls on the specially built laboratory models. The topological method and the gradient technique are used to optimization approach. The level set function was used to solve the inverse problem in the electrical impedance tomography. The...
Electrical impedance tomography (EIT) reconstructs the conductivity distribution of a domain using electrical data on its boundary. Shape derivatives and topological derivatives have been incorporated into level set methods to investigate shape optimization problems. The shape derivative measures the sensitivity of boundary perturbations while the topological derivative measures the sensitivity of...
Shape from focus technique can be used in the computer monocular vision, which is widely applied in the smart transportation. In this study, we proposed a novel directional statistics based focus measure for shape from focus computation. We first compute the standard deviation σ and the mean value μ in the directional neighborhood. Then use the σ/μ as the focus measure to estimate the shape. The proposed...
When there is the material that is high absorbency such as metal in the object, X-ray CT image often has artifacts that are abnormal findings. This artifact is called metal artifact. Metal artifact can be obstacle when examining objects accurately. Therefore, it is expected that artifact is reduced by a user of X-ray CT. To reduce metal artifact, various methods have been studied but any methods are...
Digital holograms are presented as a way to re-present and contextualise works of art that are too valuable or fragile to be transported to, and placed in, a holographic imaging system. The prototype exercise was conducted on Chinese Yuan Dynasty blue-and-white porcelain artefacts. The specific aim of the work was to explore digital holographic printing as an innovative technology to recover detailed...
A novel strategy is proposed to achieve qualitative characterization of penetrable and impenetrable objects buried in lossy soils. The approach, aimed to support reconstruction, is based on the consideration that for high conductivity and dielectric scatterers, induced and ‘equivalent’ currents can be considered localized on the boundary. In particular, an ad hoc sparsity promoting inversion approach...
It is not only interesting to predict how an individual of a relatively young age will look in the future but also to reconstruct the facial appearance in the past during childhood. It can be even more desirable when different circumstances, behavior and lifestyle and their impacts on the facial shape appearance as a consequence are taken into account. Such may be applicable for many practical reasons...
In order to better learn the distributions of 2D and 3D faces and the mapping between them with limited training samples, a new 3D face reconstruction method based on progressive cascade regression is proposed. Firstly, it learns the mapping between 2D and 3D facial landmarks to estimate the initial 3D facial landmarks with a coupled space learning method. Secondly, a deformed space is constructed...
The common challenge of all aerospace advancements is greening the air transport. This led the recent research programs towards the study of “metamorphic” wing structures, capable of adapting their geometry to the different conditions of flight. The development of morphing structures allows the reduction of drag and the increase of range, together with the growth of load control effectiveness. In...
3D Morphable Models (3DMMs) are powerful statistical models of 3D facial shape and texture, and among the state-of-the-art methods for reconstructing facial shape from single images. With the advent of new 3D sensors, many 3D facial datasets have been collected containing both neutral as well as expressive faces. However, all datasets are captured under controlled conditions. Thus, even though powerful...
Monocular 3D facial shape reconstruction from a single 2D facial image has been an active research area due to its wide applications. Inspired by the success of deep neural networks (DNN), we propose a DNN-based approach for End-to-End 3D FAce Reconstruction (UH-E2FAR) from a single 2D image. Different from recent works that reconstruct and refine the 3D face in an iterative manner using both an RGB...
We propose a novel, practical solution for high quality reconstruction of axially-symmetric transparent objects. While a special case, such transparent objects are ubiquitous in the real world. Common examples of these are glasses, goblets, tumblers, carafes, etc., that can have very unique and visually appealing forms making their reconstruction interesting for vision and graphics applications. Our...
We study the problem of learning generative models of 3D shapes. Voxels or 3D parts have been widely used as the underlying representations to build complex 3D shapes, however, voxel-based representations suffer from high memory requirements, and parts-based models require a large collection of cached or richly parametrized parts. We take an alternative approach: learning a generative model over multi-view...
Generation of 3D data by deep neural network has been attracting increasing attention in the research community. The majority of extant works resort to regular representations such as volumetric grids or collection of images, however, these representations obscure the natural invariance of 3D shapes under geometric transformations, and also suffer from a number of other issues. In this paper we address...
We present a learning framework for abstracting complex shapes by learning to assemble objects using 3D volumetric primitives. In addition to generating simple and geometrically interpretable explanations of 3D objects, our framework also allows us to automatically discover and exploit consistent structure in the data. We demonstrate that using our method allows predicting shape representations which...
The three-dimensional reconstruction of scenes from multiple views has made impressive strides in recent years, chiefly by methods correlating isolated feature points, intensities, or curvilinear structure. In the general setting, i.e., without requiring controlled acquisition, limited number of objects, abundant patterns on objects, or object curves to follow particular models, the majority of these...
Recently, researchers have made great processes to build category-specific 3D shape models from 2D images with manual annotations consisting of class labels, keypoints, and ground truth figure-ground segmentations. However, the annotation of figure-ground segmentations is still labor-intensive and time-consuming. To further alleviate the burden of providing such manual annotations, we make the earliest...
In this paper, we propose an effective face completion algorithm using a deep generative model. Different from well-studied background completion, the face completion task is more challenging as it often requires to generate semantically new pixels for the missing key components (e.g., eyes and mouths) that contain large appearance variations. Unlike existing nonparametric algorithms that search for...
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